XPySom: High-performance self-organizing maps

In this paper, we introduce XPySom, a new open-source Python implementation of the well-known Self-Organizing Maps (SOM) technique. It is designed to achieve high performance on a single node, exploiting widely available Python libraries for vector processing on multi-core CPUs and GP-GPUs. We present results from an extensive experimental evaluation of XPySom in comparison to widely used open-source SOM implementations, showing that it outperforms the other available alternatives. Indeed, our experimentation carried out using the Extended MNIST open data set shows a speed-up of about 7x and 100x when compared to the best open-source multi-core implementations we could find with multi-core and GP-GPU acceleration, respectively, achieving the same accuracy levels in terms of quantization error

Considerations of Low Carbohydrate Availability (LCA) to Relative Energy Deficiency in Sport (RED-S) in Female Endurance Athletes: A Narrative Review

The purpose of this narrative review is to identify health and performance consequences associated with LCA in female endurance athletes. The intake of carbohydrates (CHO) before, during, and after exercise has been demonstrated to support sport performance, especially endurance activities which rely extensively on CHO as a fuel source. However, low energy availability (LEA) and low carbohydrate availability (LCA) are common in female athletes. LEA occurs when energy intake is insufficient compared to exercise energy expenditure, and LEA-related conditions (e.g., Female Athlete Triad (Triad) and Relative Energy Deficiency in Sport (RED-S)) are associated with a myriad of health and performance consequences. The RED-S model highlights 10 health consequences and 10 performance consequences related to LEA. The independent effect of LCA on health and performance has been under-researched, despite current CHO intake being commonly insufficient in athletes. It is proposed that LCA may not only contribute to LEA but also have independent health and performance consequences in athletes. Furthermore, this review highlights current recommendations for CHO intake, as well as recent data on LCA prevalence and menstrual cycle considerations. A literature review was conducted on PubMed, Science Direct, and ResearchGate using relevant search terms (i.e., “low carbohydrate/energy availability”, “female distance runners”). Twenty-one articles were identified and twelve met the inclusion criteria. The total number of articles included in this review is 12, with 7 studies illustrating that LCA was associated with direct negative health and/or performance implications for endurance-based athletes. Several studies included assessed male athletes only, and no studies included a female-only study design. Overall, the cumulative data show that female athletes remain underrepresented in sports science research and that current CHO intake recommendations and strategies may fail to consider female-specific adaptations and hormone responses, such as monthly fluctuations in estrogen and progesterone throughout the menstrual cycle. Current CHO guidelines for female athletes and exercising women need to be audited and explored further in the literature to support female athlete health and performance

Behavioral analysis for virtualized network functions: A som-based approach

In this paper, we tackle the problem of detecting anomalous behaviors in a virtualized infrastructure for network function virtualization, proposing to use self-organizing maps for analyzing historical data available through a data center. We propose a joint analysis of system-level metrics, mostly related to resource consumption patterns of the hosted virtual machines, as available through the virtualized infrastructure monitoring system, and the application-level metrics published by individual virtualized network functions through their own monitoring subsystems. Experimental results, obtained by processing real data from one of the NFV data centers of the Vodafone network operator, show that our technique is able to identify specific points in space and time of the recent evolution of the monitored infrastructure that are worth to be investigated by a human operator in order to keep the system running under expected conditions

Using Self-Organizing Maps for the Behavioral Analysis of Virtualized Network Functions

Detecting anomalous behaviors in a network function virtualization infrastructure is of the utmost importance for network operators. In this paper, we propose a technique, based on Self-Organizing Maps, to address such problem by leveraging on the massive amount of historical system data that is typically available in these infrastructures. Indeed, our method consists of a joint analysis of system-level metrics, provided by the virtualized infrastructure monitoring system and referring to resource consumption patterns of the physical hosts and the virtual machines (or containers) that run on top of them, and application-level metrics, provided by the individual virtualized network functions monitoring subsystems and related to the performance levels of the individual applications. The implementation of our approach has been validated on real data coming from a subset of the Vodafone infrastructure for network function virtualization, where it is currently employed to support the decisions of data center operators. Experimental results show that our technique is capable of identifying specific points in space (i.e., components of the infrastructure) and time of the recent evolution of the monitored infrastructure that are worth to be investigated by human operators in order to keep the system running under expected conditions

Controlling the optical creation of gold nanoparticles in a PVA matrix by direct laser writing

We report about the study on the physical features of gold nano-particles (GNPs) created by 2-photons photo-reduction Direct Laser Writing in a Poly-Vinyl Alcohol (PVA) matrix doped with HAuCl4. We drop cast a film of the PVA+ HAuCl4 onto a glass substrate, in which we create 1D gratings made by stripes of GNPs with a single laser sweep. We show that the stripe width increases with the laser power and the exposure time. We also analyse the influence of the exposure time over the created nano-particles size distribution and density and we show that by suitably adjusting the exposure time it is possible to maximize the frequency of a given diameter. By comparing the experimental results with a polymerization “voxel” model, we are able to evaluate the effective cross section for 2- photons absorption of our material

Mapping the kinetic Sunyaev-Zel'dovich effect toward MACS J0717.5+3745 with NIKA

Measurement of the gas velocity distribution in galaxy clusters provides insight into the physics of mergers, through which large scale structures form in the Universe. Velocity estimates within the intracluster medium (ICM) can be obtained via the Sunyaev-Zel'dovich (SZ) effect, but its observation is challenging both in term of sensitivity requirement and control of systematic effects, including the removal of contaminants. In this paper we report resolved observations, at 150 and 260 GHz, of the SZ effect toward the triple merger MACS J0717.5+3745 (z=0.55), using data obtained with the NIKA camera at the IRAM 30m telescope. Assuming that the SZ signal is the sum of a thermal (tSZ) and a kinetic (kSZ) component and by combining the two NIKA bands, we extract for the first time a resolved map of the kSZ signal in a cluster. The kSZ signal is dominated by a dipolar structure that peaks at -5.1 and +3.4 sigma, corresponding to two subclusters moving respectively away and toward us and coincident with the cold dense X-ray core and a hot region undergoing a major merging event. We model the gas electron density and line-of-sight velocity of MACS J0717.5+3745 as four subclusters. Combining NIKA data with X-ray observations from XMM-Newton and Chandra, we fit this model to constrain the gas line-of-sight velocity of each component, and we also derive, for the first time, a velocity map from kSZ data (i.e. that is model-dependent). Our results are consistent with previous constraints on the merger velocities, and thanks to the high angular resolution of our data, we are able to resolve the structure of the gas velocity. Finally, we investigate possible contamination and systematic effects with a special care given to radio and submillimeter galaxies. Among the sources that we detect with NIKA, we find one which is likely to be a high redshift lensed submillimeter galaxy.Comment: 19 pages, 9 figures, accepted in A&

The optical design of the Litebird middle and high frequency telescope

LiteBIRD is a JAXA strategic L-class mission devoted to the measurement of polarization of the Cosmic Microwave Background, searching for the signature of primordial gravitational waves in the B-modes pattern of the polarization. The onboard instrumentation includes a Middle and High Frequency Telescope (MHFT), based on a pair of cryogenically cooled refractive telescopes covering, respectively, the 89-224 GHz and the 166-448 GHz bands. Given the high target sensitivity and the careful systematics control needed to achieve the scientific goals of the mission, optical modeling and characterization are performed with the aim to capture most of the physical effects potentially affecting the real performance of the two refractors. We describe the main features of the MHFT, its design drivers and the major challenges in system optimization and characterization. We provide the current status of the development of the optical system and we describe the current plan of activities related to optical performance simulation and validation

Observing galaxy clusters and the cosmic web through the Sunyaev Zel'dovich effect with MISTRAL

Galaxy clusters and surrounding medium, can be studied using X-ray bremsstrahlung emission and Sunyaev Zel'dovich (SZ) effect. Both astrophysical probes, sample the same environment with different parameters dependance. The SZ effect is relatively more sensitive in low density environments and thus is useful to study the filamentary structures of the cosmic web. In addition, observations of the matter distribution require high angular resolution in order to be able to map the matter distribution within and around galaxy clusters. MISTRAL is a camera working at 90GHz which, once coupled to the Sardinia Radio Telescope, can reach $12''$ angular resolution over $4'$ field of view (f.o.v.). The forecasted sensitivity is $NEFD \simeq 10-15mJy \sqrt{s}$ and the mapping speed is $MS= 380'^{2}/mJy^{2}/h$. MISTRAL was recently installed at the focus of the SRT and soon will take its first photons.Comment: To appear in Proc. of the mm Universe 2023 conference, Grenoble (France), June 2023, published by F. Mayet et al. (Eds), EPJ Web of conferences, EDP Science